Remodeling ceramide homeostasis promotes functional maturation of human pluripotent stem cell-derived ß cells.

Human pluripotent stem cell-derived ß cells (hPSC-ß cells) show the potential to restore euglycemia. However, the immature functionality of hPSC-ß cells has limited their efficacy in application. Here, by deciphering the continuous maturation process of hPSC-ß cells post transplantation via single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq), we show that functional maturation of hPSC-ß cells is an orderly multistep process during which cells sequentially undergo metabolic adaption, removal of negative regulators of cell function, and establishment of a more specialized transcriptome and epigenome. Importantly, remodeling lipid metabolism, especially downregulating the metabolic activity of ceramides, the central hub of sphingolipid metabolism, is critical for ß cell maturation. Limiting intracellular accumulation of ceramides in hPSC-ß cells remarkably enhanced their function, as indicated by improvements in insulin processing and glucose-stimulated insulin secretion. In summary, our findings provide insights into the maturation of human pancreatic ß cells and highlight the importance of ceramide homeostasis in function acquisition.

Association of early life adversity with cardiovascular disease and its potential mechanisms: a narrative review.

Strong epidemiological evidence has shown that early life adversity (ELA) has a profound negative impact on health in adulthood, including an increased risk of cardiovascular disease, the leading cause of death worldwide. Here, we review cohort studies on the effects of ELA on cardiovascular outcomes and the possible underlying mechanisms. In addition, we summarize relevant studies in rodent models of ELA. This review reveals that the prevalence of ELA varies between regions, time periods, and sexes. ELA increases cardiovascular health risk behaviors, susceptibility to mental illnesses, and neuroendocrine and immune system dysfunction in humans. Rodent models of ELA have been developed and show similar cardiovascular outcomes to those in humans but cannot fully replicate all ELA subtypes. Therefore, combining cohort and rodent studies to further investigate the mechanisms underlying the association between ELA and cardiovascular diseases may be a feasible future research strategy.

Readily releasable ß cells with tight Ca2+-exocytosis coupling dictate biphasic glucose-stimulated insulin secretion.

Biphasic glucose-stimulated insulin secretion (GSIS) is essential for blood glucose regulation, but a mechanistic model incorporating the recently identified islet ß cell heterogeneity remains elusive. Here, we show that insulin secretion is spatially and dynamically heterogeneous across the islet. Using a zinc-based fluorophore with spinning-disc confocal microscopy, we reveal that approximately 40% of islet cells, which we call readily releasable ß cells (RRßs), are responsible for 80% of insulin exocytosis events. Although glucose up to 18.2 mM fully mobilized RRßs to release insulin synchronously (first phase), even higher glucose concentrations enhanced the sustained secretion from these cells (second phase). Release-incompetent ß cells show similarities to RRßs in glucose-evoked Ca2+ transients but exhibit Ca2+-exocytosis coupling deficiency. A decreased number of RRßs and their altered secretory ability are associated with impaired GSIS progression in ob/ob mice. Our data reveal functional heterogeneity at the level of exocytosis among ß cells and identify RRßs as a subpopulation of ß cells that make a disproportionally large contribution to biphasic GSIS from mouse islets.

The physiologic complexity of beat-to-beat blood pressure is associated with age-related alterations in blood pressure regulation.

The fluctuations in resting-state beat-to-beat blood pressure (BP) are physiologically complex, and the degree of such BP complexity is believed to reflect the multiscale regulation of this critical physiologic process. Hypertension (HTN), one common age-related condition, is associated with altered BP regulation and diminished system responsiveness to perturbations such as orthostatic change. We thus aimed to characterize the impact of HTN on resting-state BP complexity, as well as the relationship between BP complexity and both adaptive capacity and underlying vascular characteristics. We recruited 392 participants (age: 60-91 years), including 144 that were normotensive and 248 with HTN (140 controlled- and 108 uncontrolled-HTN). Participants completed a 10-min continuous finger BP recording during supine rest, then underwent measures of lying-to-standing BP change, arterial stiffness (i.e., brachial-ankle pulse wave velocity), and endothelial function (i.e., flow-mediated vasodilation). The complexity of supine beat-to-beat systolic (SBP) and diastolic (DBP) BP was quantified using multiscale entropy. Thirty participants with HTN (16 controlled-HTN and 14 uncontrolled-HTN) exhibited orthostatic hypotension. SBP and DBP complexity was greatest in normotensive participants, lower in those with controlled-HTN, and lowest in those in uncontrolled-HTN (p < 0.0005). Lower SBP and DBP complexity correlated with greater lying-to-standing decrease in SBP and DBP level (ß = -0.33 to -0.19, p < 0.01), greater arterial stiffness (ß = -0.35 to -0.18, p < 0.01), and worse endothelial function (ß = 0.17-0.22, p < 0.01), both across all participants and within the control- and uncontrolled-HTN groups. These results suggest that in older adults, BP complexity may capture the integrity of multiple interacting physiologic mechanisms that regulate BP and are important to cardiovascular health.

A tool kit of highly selective and sensitive genetically encoded neuropeptide sensors.

Neuropeptides are key signaling molecules in the endocrine and nervous systems that regulate many critical physiological processes. Understanding the functions of neuropeptides in vivo requires the ability to monitor their dynamics with high specificity, sensitivity, and spatiotemporal resolution. However, this has been hindered by the lack of direct, sensitive, and noninvasive tools. We developed a series of GRAB (G protein-coupled receptor activation‒based) sensors for detecting somatostatin (SST), corticotropin-releasing factor (CRF), cholecystokinin (CCK), neuropeptide Y (NPY), neurotensin (NTS), and vasoactive intestinal peptide (VIP). These fluorescent sensors, which enable detection of specific neuropeptide binding at nanomolar concentrations, establish a robust tool kit for studying the release, function, and regulation of neuropeptides under both physiological and pathophysiological conditions.

Bright and sensitive red voltage indicators for imaging action potentials in brain slices and pancreatic islets.

Genetically encoded voltage indicators (GEVIs) allow the direct visualization of cellular membrane potential at the millisecond time scale. Among these, red-emitting GEVIs have been reported to support multichannel recordings and manipulation of cellular activities with reduced autofluorescence background. However, the limited sensitivity and dimness of existing red GEVIs have restricted their applications in neuroscience. Here, we report a pair of red-shifted opsin-based GEVIs, Cepheid1b and Cepheid1s, with improved dynamic range, brightness, and photostability. The improved dynamic range is achieved by a rational design to raise the electrochromic Förster resonance energy transfer efficiency, and the higher brightness and photostability are approached with separately engineered red fluorescent proteins. With Cepheid1 indicators, we recorded complex firings and subthreshold activities of neurons on acute brain slices and observed heterogeneity in the voltage­calcium coupling on pancreatic islets. Overall, Cepheid1 indicators provide a strong tool to investigate excitable cells in various sophisticated biological systems.

Functional connectivity changes are correlated with sleep improvement in chronic insomnia patients after rTMS treatment.

Background: Repetitive transcranial magnetic stimulation (rTMS) has been increasingly used as a treatment modality for chronic insomnia disorder (CID). However, our understanding of the mechanisms underlying the efficacy of rTMS is limited. Objective: This study aimed to investigate rTMS-induced alterations in resting-state functional connectivity and to find potential connectivity biomarkers for predicting and tracking clinical outcomes after rTMS. Methods: Thirty-seven patients with CID received a 10-session low frequency rTMS treatment applied to the right dorsolateral prefrontal cortex. Before and after treatment, the patients underwent resting-state electroencephalography recordings and a sleep quality assessment using the Pittsburgh Sleep Quality Index (PSQI). Results: After treatment, rTMS significantly increased the connectivity of 34 connectomes in the lower alpha frequency band (8-10 Hz). Additionally, alterations in functional connectivity between the left insula and the left inferior eye junction, as well as between the left insula and medial prefrontal cortex, were associated with a decrease in PSQI score. Further, the correlation between the functional connectivity and PSQI persisted 1 month after the completion of rTMS as evidenced by subsequent electroencephalography (EEG) recordings and the PSQI assessment. Conclusion: Based on these results, we established a link between alterations in functional connectivity and clinical outcomes of rTMS, which suggested that EEG-derived functional connectivity changes were associated with clinical improvement of rTMS in treating CID. These findings provide preliminary evidence that rTMS may improve insomnia symptoms by modifying functional connectivity, which can be used to inform prospective clinical trials and potentially for treatment optimization.

Dual-targeted repetitive transcranial magnetic stimulation modulates brain functional network connectivity to improve cognition in mild cognitive impairment patients.

Background: Mild cognitive impairment (MCI) is a condition between normal aging and dementia; nearly 10-15% of MCI patients develop dementia annually. There are no effective interventions for MCI progression. Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive brain stimulation technique that has attempted to improve the overall cognitive function of MCI patients. However, it does not affect episodic memory improvement. Methods: In this study, we engaged 15 clinically diagnosed MCI patients and normal controls to explore the effect of dual-targeted rTMS on progressing cognitive function, particularly episodic memory in MCI patients. Resting-state EEG recordings and neuropsychological assessments were conducted before and after the intervention. EEG features were extracted using an adaptive algorithm to calculate functional connectivity alterations in relevant brain regions and the mechanisms of altered brain functional networks in response to dual-target rTMS. Results: The study revealed that the functional brain connectivity between the right posterior cingulate gyrus (PCC) and the right dorsal caudate nucleus (DC) was significantly reduced in MCI patients compared to normal controls (p < 0.001). Dual-target rTMS increased the strength of the reduced functional connectivity (p < 0.001), which was related to cognitive enhancement (p < 0.05). Conclusion: This study provides a new stimulation protocol for rTMS intervention. Improving the functional connectivity of the right PCC to the right DC is a possible mechanism by which rTMS improves overall cognitive and memory function in MCI patients.

Pancreatic α and ß cells are globally phase-locked.

The Ca2+ modulated pulsatile glucagon and insulin secretions by pancreatic α and ß cells play a crucial role in glucose homeostasis. However, how α and ß cells coordinate to produce various Ca2+ oscillation patterns is still elusive. Using a microfluidic device and transgenic mice, we recorded Ca2+ signals from islet α and ß cells, and observed heterogeneous Ca2+ oscillation patterns intrinsic to each islet. After a brief period of glucose stimulation, α and ß cells' oscillations were globally phase-locked. While the activation of α cells displayed a fixed time delay of ~20 s to that of ß cells, ß cells activated with a tunable period. Moreover, islet α cell number correlated with oscillation frequency. We built a mathematical model of islet Ca2+ oscillation incorporating paracrine interactions, which quantitatively agreed with the experimental data. Our study highlights the importance of cell-cell interaction in generating stable but tunable islet oscillation patterns.

A Multiclassifier System to Identify and Subtype Congenital Adrenal Hyperplasia Based on Circulating Steroid Hormones.

CONTEXT: Measurement of plasma steroids is necessary for diagnosis of congenital adrenal hyperplasia (CAH). We sought to establish an efficient strategy for detection and subtyping of CAH with a machine-learning algorithm. METHODS: Clinical phenotype and genetic testing were used to provide CAH diagnosis and subtype. We profiled 13 major steroid hormones by liquid chromatography-tandem mass spectrometry. A multiclassifier system was established to distinguish 11ß-hydroxylase deficiency (11ßOHD), 17α-hydroxylase/17,20-lyase deficiency (17OHD), and 21α-hydroxylase deficiency (21OHD) in a discovery cohort (n = 226). It was then validated in an independent cohort (n = 111) and finally applied in a perspective cohort of 256 patients. The diagnostic performance on the basis of area under receiver operating characteristic curves (AUCs) was evaluated. RESULTS: A cascade logistic regression model, we named the "Steroidogenesis Score", was able to discriminate the 3 most common CAH subtypes: 11ßOHD, 17OHD, and 21OHD. In the perspective application cohort, the steroidogenesis score had a high diagnostic accuracy for all 3 subtypes, 11ßOHD (AUC, 0.994; 95% CI, 0.983-1.000), 17OHD (AUC, 0.993; 95% CI, 0.985-1.000), and 21OHD (AUC, 0.979; 95% CI, 0.964-0.994). For nonclassic 21OHD patients, the tool presented with significantly higher sensitivity compared with measurement of basal 17α-hydroxyprogesterone (17OHP) (0.973 vs 0.840, P = 0.005) and was not inferior to measurement of basal vs stimulated 17OHP (0.973 vs 0.947, P = 0.681). CONCLUSIONS: The steroidogenesis score was biochemically interpretable and showed high accuracy in identifying CAH patients, especially for nonclassic 21OHD patients, thus offering a standardized approach to diagnose and subtype CAH.

Human pluripotent stem-cell-derived islets ameliorate diabetes in non-human primates.

Human pluripotent stem-cell-derived islets (hPSC-islets) are a promising cell resource for diabetes treatment1,2. However, this therapeutic strategy has not been systematically assessed in large animal models physiologically similar to humans, such as non-human primates3. In this study, we generated islets from human chemically induced pluripotent stem cells (hCiPSC-islets) and show that a one-dose intraportal infusion of hCiPSC-islets into diabetic non-human primates effectively restored endogenous insulin secretion and improved glycemic control. Fasting and average pre-prandial blood glucose levels significantly decreased in all recipients, accompanied by meal or glucose-responsive C-peptide release and overall increase in body weight. Notably, in the four long-term follow-up macaques, average hemoglobin A1c dropped by over 2% compared with peak values, whereas the average exogenous insulin requirement reduced by 49% 15 weeks after transplantation. Collectively, our findings show the feasibility of hPSC-islets for diabetic treatment in a preclinical context, marking a substantial step forward in clinical translation of hPSC-islets.

Cell-to-cell variability in inducible Caspase9-mediated cell death.

iCasp9 suicide gene has been widely used as a promising killing strategy in various cell therapies. However, different cells show significant heterogeneity in response to apoptosis inducer, posing challenges in clinical applications of killing strategy. The cause of the heterogeneity remains elusive so far. Here, by simultaneously monitoring the dynamics of iCasp9 dimerization, Caspase3 activation, and cell fate in single cells, we found that the heterogeneity was mainly due to cell-to-cell variability in initial iCasp9 expression and XIAP/Caspase3 ratio. Moreover, multiple-round drugging cannot increase the killing efficiency. Instead, it will place selective pressure on protein levels, especially on the level of initial iCasp9, leading to drug resistance. We further show this resistance can be largely eliminated by combinatorial drugging with XIAP inhibitor at the end, but not at the beginning, of the multiple-round treatments. Our results unveil the source of cell fate heterogeneity and drug resistance in iCasp9-mediated cell death, which may enlighten better therapeutic strategies for optimized killing.

Effects of Repetitive Transcranial Magnetic Stimulation in Patients With Mild Cognitive Impairment: A Meta-Analysis of Randomized Controlled Trials.

Background: Mild cognitive impairment (MCI) is an intermediary state between normal aging and dementia. It has a high risk of progression in patients with Alzheimer's disease (AD). Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive brain stimulation technique used to improve cognitive deficits in patients with MCI and AD. Although previous meta-analyses included studies carried on patients with MCI and AD, few studies have analyzed patients with MCI independently. This meta-analysis aimed to evaluate the effects and safety of rTMS on cognition function in patients with MCI and factors that may influence such effects. Methods: Data used in this study were searched and screened from different databases, including PubMed, Web of Science, Embase, the Cochrane Library, Chinese National Knowledge Infrastructure (CNKI), Chinese Technical Periodicals (VIP), Wanfang Database, and China BioMedical Literature Database (SinoMed). The retrieved studies were carefully reviewed, data were extracted, and the quality of data was assessed. Results: A total of 12 studies involving 329 patients with MCI were included in the present meta-analysis. The analyses results revealed that rTMS improved cognitive function [standardized mean difference (SMD) = 0.83, 95% confidence interval (CI) = 0.44-1.22, p = 0.0009] and memory function (SMD = 0.73, 95% CI = 0.48-0.97, p < 0.00001) in the MCI + rTMS active group when compared to the sham stimulation group. The showed that: (1) cognitive improvement was more pronounced under high-frequency rTMS stimulation of multiple sites, such as the bilateral dorsolateral prefrontal cortex and (2) more than 10 rTMS stimulation sessions produced higher improvement on cognition function in patients with MCI. Conclusions: This study shows that rTMS can improve cognitive function in patients with MCI, especially when applied at high frequency, multi-site, and for a prolonged period. However, further studies are required to validate these findings and explore more effective stimulation protocols and targets. Systematic Review Registration: [http://www.crd.york.ac.uk/PROSPERO/], identifier: CRD 42021238708.

Red- and Far-Red-Emitting Zinc Probes with Minimal Phototoxicity for Multiplexed Recording of Orchestrated Insulin Secretion.

Zinc biology, featuring intertwining signaling networks and critical importance to human health, witnesses exciting opportunities in the big data era of physiology. Here, we report a class of red- and far-red-emitting Zn2+ probes with Kd values ranging from 190 nM to 74 µM, which are particularly suitable for real-time monitoring the high concentration of Zn2+ co-released with insulin during vesicular secretory events. Compared to the prototypical rhodamine-based Zn2+ probes, the new class exploits morpholino auxochromes which eliminates phototoxicity during long-term live recording of isolated islets. A Si-rhodamine-based Zn2+ probe with high turn-on ratio (>100), whose synthesis was enabled by a new route featuring late-stage N-alkylation, allowed simultaneous recording of Ca2+ influx, mitochondrial signal, and insulin secretion in isolated mouse islets. The time-lapse multicolor fluorescence movies and their analysis, enabled by red-shifted Zn2+ and other orthogonal physiological probes, highlight the potential impact of biocompatible fluorophores on the fields of islet endocrinology and system biology.

Repetitive Transcranial Magnetic Stimulation of the Dorsolateral Prefrontal Cortex Modulates Electroencephalographic Functional Connectivity in Alzheimer's Disease.

Background: Increasing evidence demonstrates that repetitive transcranial magnetic stimulation (rTMS) treatment of the dorsolateral prefrontal cortex is beneficial for improving cognitive function in patients with Alzheimer's disease (AD); however, the underlying mechanism of its therapeutic effect remains unclear. Objectives/Hypothesis: The aim of this study was to investigate the impact of rTMS to the dorsolateral prefrontal cortex on functional connectivity along with treatment response in AD patients with different severity of cognitive impairment. Methods: We conducted a 2-week treatment course of 10-Hz rTMS over the left dorsolateral prefrontal cortex in 23 patients with AD who were split into the mild or moderate cognitive impairment subgroup. Resting state electroencephalography and general cognition was assessed before and after rTMS. Power envelope connectivity was used to calculate functional connectivity at the source level. The functional connectivity of AD patients and 11 cognitively normal individuals was compared. Results: Power envelope connectivity was higher in the delta and theta bands but lower in the beta band in the moderate cognitive impairment group, compared to the cognitively normal controls, at baseline (p < 0.05). The mild cognitive impairment group had no significant abnormities. Montreal Cognitive Assessment scores improved after rTMS in the moderate and mild cognitive impairment groups. Power envelope connectivity in the beta band post-rTMS was increased in the moderate group (p < 0.05) but not in the mild group. No significant changes in the delta and theta band were found after rTMS in both the moderate and mild group. Conclusion: High-frequency rTMS to the dorsolateral prefrontal cortex modulates electroencephalographic functional connectivity while improving cognitive function in patients with AD. Increased beta connectivity may have an important mechanistic role in rTMS therapeutic effects.

Classification of Cognitive Impairment and Healthy Controls Based on Transcranial Magnetic Stimulation Evoked Potentials.

Backgrounds: Nowadays, risks of Cognitive Impairment (CI) [highly suspected Alzheimer's disease (AD) in this study] threaten the quality of life for more older adults as the population ages. The emergence of Transcranial Magnetic Stimulation-Electroencephalogram (TMS-EEG) enables noninvasive neurophysiological investi-gation of the human cortex, which might be potentially used for CI detection. Objectives: The aim of this study is to explore whether the spatiotemporal features of TMS Evoked Potentials (TEPs) could classify CI from healthy controls (HC). Methods: Twenty-one patients with CI and 22 HC underwent a single-pulse TMS-EEG stimulus in which the pulses were delivered to the left dorsolateral prefrontal cortex (left DLPFC). After preprocessing, seven regions of interest (ROIs) and two most reliable TEPs' components: N100 and P200 were selected. Next, seven simple and interpretable linear features of TEPs were extracted for each region, three common machine learning algorithms including Support Vector Machine (SVM), Random Forest (RF), and K-Nearest Neighbor (KNN) were used to detect CI. Meanwhile, data augmentation and voting strategy were used for a more robust model. Finally, the performance differences of features in classifiers and their contributions were investigated. Results: 1. In the time domain, the features of N100 had the best performance in the SVM classifier, with an accuracy of 88.37%. 2. In the aspect of spatiality, the features of the right frontal region and left parietal region had the best performance in the SVM classifier, with an accuracy of 83.72%. 3. The Local Mean Field Power (LMFP), Average Value (AVG), Latency and Amplitude contributed most in classification. Conclusions: The TEPs induced by TMS over the left DLPFC has significant differences spatially and temporally between CI and HC. Machine learning based on the spatiotemporal features of TEPs have the ability to separate the CI and HC which suggest that TEPs has potential as non-invasive biomarkers for CI diagnosis.

Application of Structural and Functional Connectome Mismatch for Classification and Individualized Therapy in Alzheimer Disease.

While machine learning approaches to analyzing Alzheimer disease connectome neuroimaging data have been studied, many have limited ability to provide insight in individual patterns of disease and lack the ability to provide actionable information about where in the brain a specific patient's disease is located. We studied a cohort of patients with Alzheimer disease who underwent resting state functional magnetic resonance imaging and diffusion tractography imaging. These images were processed, and a structural and functional connectivity matrix was generated using the HCP cortical and subcortical atlas. By generating a machine learning model, individual-level structural and functional anomalies detection and characterization were explored in this study. Our study found that structural disease burden in Alzheimer's patients is mainly focused in the subcortical structures and the Default mode network (DMN). Interestingly, functional anomalies were less consistent between individuals and less common in general in these patients. More intriguing was that some structural anomalies were noted in all patients in the study, namely a reduction in fibers involving parcellations in the right anterior cingulate. Alternately, the functional consequences of connectivity loss were cortical and variable. Integrated structural/functional connectomics might provide a useful tool for assessing AD progression, while few concerns have been made for analyzing the mismatch between these two. We performed a preliminary exploration into a set of Alzheimer disease data, intending to improve a personalized approach to understanding individual connectomes in an actionable manner. Specifically, we found that there were consistent patterns of white matter fiber loss, mainly focused around the DMN and deep subcortical structures, which were present in nearly all patients with clinical AD. Functional magnetic resonance imaging shows abnormal functional connectivity different within the patients, which may be used as the individual target for further therapeutic strategies making, like non-invasive stimulation technology.

Alzheimer's Disease Classification With a Cascade Neural Network.

Classification of Alzheimer's Disease (AD) has been becoming a hot issue along with the rapidly increasing number of patients. This task remains tremendously challenging due to the limited data and the difficulties in detecting mild cognitive impairment (MCI). Existing methods use gait [or EEG (electroencephalogram)] data only to tackle this task. Although the gait data acquisition procedure is cheap and simple, the methods relying on gait data often fail to detect the slight difference between MCI and AD. The methods that use EEG data can detect the difference more precisely, but collecting EEG data from both HC (health controls) and patients is very time-consuming. More critically, these methods often convert EEG records into the frequency domain and thus inevitably lose the spatial and temporal information, which is essential to capture the connectivity and synchronization among different brain regions. This paper proposes a cascade neural network with two steps to achieve a faster and more accurate AD classification by exploiting gait and EEG data simultaneously. In the first step, we propose attention-based spatial temporal graph convolutional networks to extract the features from the skeleton sequences (i.e., gait) captured by Kinect (a commonly used sensor) to distinguish between HC and patients. In the second step, we propose spatial temporal convolutional networks to fully exploit the spatial and temporal information of EEG data and classify the patients into MCI or AD eventually. We collect gait and EEG data from 35 cognitively health controls, 35 MCI, and 17 AD patients to evaluate our proposed method. Experimental results show that our method significantly outperforms other AD diagnosis methods (91.07 vs. 68.18%) in the three-way AD classification task (HC, MCI, and AD). Moreover, we empirically found that the lower body and right upper limb are more important for the early diagnosis of AD than other body parts. We believe this interesting finding can be helpful for clinical researches.

Metabolomics study of the anti-inflammatory effects of endogenous omega-3 polyunsaturated fatty acids.

Low-grade inflammation is usually defined as the chronic production and a low-grade state of inflammatory factors, it often does not have symptoms, and has been associated with neurodegenerative disease, obesity, and diabetes. Omega-3 polyunsaturated fatty acids (n-3 PUFAs) are the precursors of many anti-inflammatory metabolites, such as resolvins and neuroprotectins. It is of interest to study the metabolic profile of endogenous n-3 PUFAs in low-grade inflammatory conditions. To evaluate the protective effects of endogenous n-3 PUFAs on low-grade inflammation with the metabolomics approach, we fed fat-1 mice with an n-6 PUFAs rich diet for a long time to induce a low-grade inflammatory condition. Multi-analysis techniques, including structural analysis using quadrupole time-of-flight mass spectrometry with MSE mode, were applied in untargeted metabolomics to search for meaningful metabolites with significant variance in fat-1 mice under low-grade inflammation. Following the untargeted metabolomics screening, several meaningful metabolites were selected which were associated with anti-inflammatory effects generated from endogenous n-3 PUFAs for further analysis. The results revealed that the purine metabolism, fatty acid metabolism and oxidative stress response pathways through insulin resistance were involved in anti-inflammatory mechanisms of n-3 PUFA in low-grade inflammatory conditions. For the first time, this study explored the highlighted pathways as contributors to the anti-inflammatory effects of endogenous n-3 PUFAs in low-grade inflammatory conditions.

Fish oil treatment reduces chronic alcohol exposure induced synaptic changes.

Alcohol addiction is a chronic neuropsychiatric disorder that represents one of the most serious global public health problems. Yet, currently there still lacks an effective pharmacotherapy. Omega-3 polyunsaturated fatty acids (N-3 PUFAs) have exhibited beneficial effects in a variety of neurological disorders, particularly in reversing behavioral deficits and neurotoxicity induced by prenatal alcohol exposure and binge drinking. In the present study, we investigated if fish oil, which is rich in N-3 PUFAs, had beneficial effects on preventing relapse and alleviating withdrawal symptoms after chronic alcohol exposure. Our results demonstrated that fish oil significantly reduced the chronic alcohol exposure-induced aberrant dendritic morphologic changes of the medium-sized spiny neurons in the core and the shell of nucleus accumbens. This inhibited the expression of AMPAR2-lacking AMPARs and their accumulation on the post synaptic membranes of medium-sized spiny neurons and eventually alleviated withdrawal symptoms and alcohol dependence. Our study therefore suggests that N-3 PUFAs are promising for treating withdrawal symptoms and alcohol dependence.